collaborators

6 papers

cs.SD2026

AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation

Zeyue Tian, Lei Ke, Zhaoyang Liu +8

Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…

eess.AS2026

Which Speech Representation Better Matches Text-Native Reasoning? A Study of Speech-Text Alignment on Frame Rate and Representation

Zhen Ye, Xu Tan, Yiming Li +10

Spoken dialogue models typically start from text LLM backbones, yet reasoning often degrades when conditioning on speech instead of text. We attribute part of this modality gap to…

cs.CV2026

Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling

Zhen Ye, Xu Tan, Aoxiong Yin +8

Joint audio-video generation models have shown that unified generation yields stronger cross-modal coherence than cascaded approaches. However, existing models couple modalities th…

cs.MM2026

AudioX: A Unified Framework for Anything-to-Audio Generation

Zeyue Tian, Zhaoyang Liu, Yizhu Jin +6

Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…

cs.CV2025

VidMuse: A Simple Video-to-Music Generation Framework with Long-Short-Term Modeling

Zeyue Tian, Zhaoyang Liu, Ruibin Yuan +6

In this work, we systematically study music generation conditioned solely on the video. First, we present a large-scale dataset comprising 360K video-music pairs, including various…

eess.AS2025

Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis

Zhen Ye, Xinfa Zhu, Chi-Min Chan +17

Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…